Genetic Optimisation of C++ Applications

Rafail Giavrimis, Alexis Butler, Constantin Cezar Petrescu, Michail Basios, Santanu Kumar Dash

DOI 10.1109/ase51524.2021.9678650 dblp

Abstract

Software developers sometimes use inefficient data structures or library interfaces without considering the potential impact they may have during the runtime of a program. This is due to the significant effort required to research and evaluate possibly more eﬃcient alternatives. Consequently, there is a need for tooling to automate the design space exploration. Our proposed code optimisation solution, called Artemis++, tries to address this issue with automatic exploration and transformation of data structures to optimise software performance. In preliminary testing on three mainstream C++ libraries, we have observed improvements up to 16.09%, 27.90%, and 2.74% for CPU usage, runtime and memory, respectively.

BibTeX

@inproceedings{Giavrimis-al:ASE21,
  author    = {Rafail Giavrimis and
               Alexis Butler and
               Constantin Cezar Petrescu and
               Michail Basios and
               Santanu Kumar Dash},
  title     = {Genetic Optimisation of C++ Applications},
  booktitle = {ASE},
  pages     = {1180--1182},
  publisher = {{IEEE}},
  year      = {2021},
}

Genetic Optimisation of C++ Applications

Abstract

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